The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Finding the WRITE stuff: automatic identification of discourse structure in student essays
Abstract
An essay-based discourse analysis system can help students improve their writing by identifying relevant essay-based discourse elements in their essays. Our discourse analysis software, which is embedded in Criterion, an online essay evaluation application, uses machine learning to identify discourse elements in student essays. The system makes decisions that exemplify how teachers perform this task. For instance, when grading student essays, teachers comment on the discourse structure. Teachers might explicitly state that the essay lacks a thesis statement or that an essay's single main idea has insufficient support. Training the systems to model this behavior requires human judges to annotate a data sample of student essays. The annotation schema reflects the highly structured discourse of genres such as persuasive writing. Our discourse analysis system uses a voting algorithm that takes into account the discourse labeling decisions of three independent systems.
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Rhetorical Structure Theory: Toward a functional theory of text organization
MANN, W. C., & THOMPSON, S. A. (1988) · Text - Interdisciplinary Journal for the Study of Discourse · doi:10.1515/text.1.1988.8.3.243 · Cited by 3,853
Cited by
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Attali, Y., & Burstein, J. (2004) · ETS Research Report Series · doi:10.1002/j.2333-8504.2004.tb01972.x · Cited by 622
Self-citationAutomated writing evaluation: Defining the classroom research agenda
Warschauer, M., & Ware, P. (2006) · Language Teaching Research · doi:10.1191/1362168806lr190oa · Cited by 337
(2004) · Cited by 128
Potential of automated writing evaluation feedback
Cotos, E. (2011) · CALICO Journal · doi:10.11139/cj.28.2.420-459 · Cited by 95
The Effect of Using Automated Essay Evaluation on ESL Undergraduate Students’ Writing Skill
Aluthman, E. S. (2016) · International Journal of English Linguistics · doi:10.5539/ijel.v6n5p54 · Cited by 45
Metadata
- Authors
- Burstein, J., Marcu, D., & Knight, K.
- Venue
- IEEE Intelligent Systems
- Published
- 2003-01
- Volume
- 18
- Issue
- 1
- Pages
- 32-39
- ISSN
- 1541-1672 (ISSN-L)
- OpenAlex
- W2018896856
- Cited by
- 189
- References
- 1
- FWCI
- 9.89
- Type
- journal article
- Language
- en
- Open access
- closed
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